TY - GEN
T1 - Integration of accent sandhi and prosodic features estimation for japanese text-to-speech synthesis
AU - Fujimaki, Daisuke
AU - Nose, Takashi
AU - Ito, Akinori
N1 - Funding Information:
A part of this work was supported by the JST COI Grant Number JPMJCE1303 and the JSPS Grant-in-Aid for Scientific Research JP17H00823.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - In recent years, Japanese text-to-speech (TTS) synthesis methods have been actively researched. We need to estimate appropriate prosodic information for generating a high-quality synthetic speech. However, manual annotation is costly, and automatic annotation introduces estimation errors. This paper examines the integration of accent sandhi and prosodic feature estimation in the acoustic modeling for Japanese TTS to overcome the problems. The proposed method achieves total optimization of the F0 model by using the linguistic features from a dictionary. Objective and subjective evaluations confirmed that the cost of creating accent labels was reduced, and the accuracy of the prosodic feature estimation was improved.
AB - In recent years, Japanese text-to-speech (TTS) synthesis methods have been actively researched. We need to estimate appropriate prosodic information for generating a high-quality synthetic speech. However, manual annotation is costly, and automatic annotation introduces estimation errors. This paper examines the integration of accent sandhi and prosodic feature estimation in the acoustic modeling for Japanese TTS to overcome the problems. The proposed method achieves total optimization of the F0 model by using the linguistic features from a dictionary. Objective and subjective evaluations confirmed that the cost of creating accent labels was reduced, and the accuracy of the prosodic feature estimation was improved.
KW - accent sandhi
KW - Japanese text-to-speech
KW - speech synthesis
UR - http://www.scopus.com/inward/record.url?scp=85099400947&partnerID=8YFLogxK
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U2 - 10.1109/GCCE50665.2020.9291906
DO - 10.1109/GCCE50665.2020.9291906
M3 - Conference contribution
AN - SCOPUS:85099400947
T3 - 2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
SP - 358
EP - 359
BT - 2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE Global Conference on Consumer Electronics, GCCE 2020
Y2 - 13 October 2020 through 16 October 2020
ER -